Characterizing the multi-scale variations of tropical convective clouds with multi-satellite data fusion

Tropical convective clouds play a critical role in heat and moisture transport from the planetary boundary layer to the upper troposphere and even lower stratosphere. However, there are still large biases in GCM-simulated tropical precipitation, which indicates the need for our improved understanding of convection and associated detrainment processes. By collocating Aqua passive measurements with CloudSat and CALIPSO active cloud measurements, we develop a new infrared (IR) based method to effectively separate convective core and thick anvils by selecting proper thresholds for 11 brightness temperature (BT11) and the difference between 6.7 brightness temperature (BT6.7) and BT11. The thresholds account for the seasonal and regional upper troposphere temperature changes as well. This new method could be further used for geostationary satellite to provide needed spatial and temporal coverage to study convective cloud variations. Given the fact that A-Train satellite measurements are widely used for tropical convective cloud study, the potential sampling biases are documented as well. The spatial sampling biases of CloudSat and CALIPSO measurements are evaluated with wide swath MODIS measurements. And the 3-hourly geostationary satellite measurements are used to evaluate MODIS potential temporal sampling biases for tropical convective cloud studies. The synergy of these satellite measurements is used to characterize the multi-scale variations of tropical convective clouds.